Digital Agriculture Sandbox for Collaborative Research
Osama Zafar, Rosemarie Santa Gonz\'alez, Alfonso Morales, and Erman Ayday

TL;DR
The paper introduces the Digital Agriculture Sandbox, a secure platform that facilitates privacy-preserving collaboration between farmers and researchers using advanced techniques like federated learning and differential privacy.
Contribution
It presents a novel online platform that enables secure, privacy-preserving data sharing and analysis for digital agriculture research, addressing farmers' privacy concerns.
Findings
Enables farmers to share data securely without exposing private info.
Allows researchers to analyze farm data while maintaining privacy.
Facilitates collaboration between farmers and researchers for agricultural improvements.
Abstract
Digital agriculture is transforming the way we grow food by utilizing technology to make farming more efficient, sustainable, and productive. This modern approach to agriculture generates a wealth of valuable data that could help address global food challenges, but farmers are hesitant to share it due to privacy concerns. This limits the extent to which researchers can learn from this data to inform improvements in farming. This paper presents the Digital Agriculture Sandbox, a secure online platform that solves this problem. The platform enables farmers (with limited technical resources) and researchers to collaborate on analyzing farm data without exposing private information. We employ specialized techniques such as federated learning, differential privacy, and data analysis methods to safeguard the data while maintaining its utility for research purposes. The system enables farmers…
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Taxonomy
TopicsSmart Agriculture and AI · Privacy-Preserving Technologies in Data · ICT in Developing Communities
